Recognizing Real Customers in E-Supply Chain Based on SOFM Neural Network and Corresponding Marketing Strategies

In today\´s buyers\´ market, "the customer is God", the competition is no longer enterprise to enterprise, but supply chain to supply chain. So exactly to recognize real customer in e-supply chain is the key factor to success for assuring the profit of the whole e-supply chain. There is a large amount of consuming data stored in the e-supply chain everyday. If one e-supply chain can make full use of these valuable data on the Internet to recognize its real customers and target these customers\´ features of consuming behaviors to produce, sell, distribute, and offer a integrated individualized service from the whole e-supply chain, this greatly increases the loyalty of customers of the e-supply chain, maximize the profit of the whole e-supply chain, and make the e-supply chain more competitive in the world. In this paper, SOFM neural network is employed as a tool to mine these valuable consuming data in the e-supply chain for recognizing its real customers. The SOFM neural network is a novel and very interesting approach that can resemble recognition function of the brain. By mean of the SOFM neural network\´s approach, these most-downstream customers in e-supply chain can be objectively, scientifically and automatically clustered and divided into different groups. Besides, based on the scientific recognition and analysis of customers\´ consuming behaviors from these different groups, there are some corresponding marketing strategies to be suggested just for references